Congested Emergency Evacuation of a Population Using a Finite Automata Approach

In this paper, we address a model for population evacuation during a congested emergency event. The model employs cellular automata for space modeling and the Schadschneider model to derive the transition probabilities for the motion of the pedestrians. We describe an extension of the transition probability model that includes a component to take into account the intuitive idea that speed can be considered a direct function of population density in the modeled environment. A simulation program was encoded in C++ because of the efficiency, portability, and robustness of the programming language; the program is available from the authors upon request for educational and research purposes. A real situation was modeled and simulated with the program. All the data generated were analyzed to show the efficiency and accuracy of the new approach. Interesting new insights emerged from this analysis; notably, the results obtained are consistent with a well-known extreme value distribution.